CN117120283A

CN117120283A - Improved vehicle motion management based on dynamic tire models

Info

Publication number: CN117120283A
Application number: CN202180096752.0A
Authority: CN
Inventors: 里奥·莱恩; 里昂·亨德森; 乌尔夫·斯滕布拉特; 阿迪耶·阿里凯雷; 马茨·吕德斯特伦; 奇丹巴拉姆·萨布拉马尼安
Original assignee: Volvo Truck Corp
Current assignee: Volvo Truck Corp
Priority date: 2021-04-07
Filing date: 2021-04-07
Publication date: 2023-11-24
Also published as: WO2022214174A1; US20240182041A1; JP2024517378A; EP4319996A1; KR20230167362A

Abstract

A method for controlling movement of a heavy vehicle (100), the method comprising: obtaining input data related to one or more parameters of a tire (150, 160, 170) on a heavy vehicle (100), determining at least a portion of the one or more tire parameters based on the input data, configuring a tire model, wherein the tire model defines a relationship between wheel slip and generated wheel force, wherein the tire model is parameterized by the one or more tire parameters, and controlling movement of the heavy vehicle based on the relationship between wheel slip and generated wheel force.

Description

Improved vehicle motion management based on dynamic tire models

Technical Field

The present disclosure relates to a method and a control unit for ensuring safe and efficient vehicle motion management of a heavy vehicle. The method is particularly suitable for use with articulated vehicles, such as trucks and semi-trailers comprising a plurality of vehicle units. However, the invention is also applicable to other types of heavy vehicles, such as construction equipment and mining vehicles.

Background

Heavy vehicles (such as trucks and semi-trailer vehicles) are designed to carry heavy loads. Heavy-duty vehicles must be able to start from a stationary state, also in uphill conditions, accelerate on various types of road surfaces and, above all, be able to slow down, i.e. brake, in a controlled and reliable manner at any time. It is also important that the vehicle is able to operate in an energy efficient manner without unnecessary wear of components. A key feature to achieving this function is a well-designed set of tires. Accordingly, much work has been done in developing tires for heavy vehicles, where well-designed tires provide a combination of high friction and low rolling resistance. Well-designed tires also have a low wear rate, i.e., are mechanically durable and have a long service life.

Excessive wheel slip occurs when the torque applied to the axle or wheels is excessive compared to the road friction. Excessive wheel slip is undesirable because it can lead to unpredictable vehicle behavior and energy-inefficient operation.

GB 2562308A discusses wheel slip and proposes a method for limiting the maximum regenerative braking torque that can be applied to the wheels. The controller uses the tire model to determine the maximum available traction for each wheel and calculates the maximum regenerative braking force to be applied to each wheel based on the tire model.

However, there is still a need for further improvements in vehicle motion management for heavy vehicles.

Disclosure of Invention

It is an object of the present disclosure to provide techniques that alleviate or overcome at least some of the above-mentioned problems. This object is at least partly achieved by a method for controlling the movement of a heavy vehicle. The method comprises the following steps: obtaining input data related to one or more parameters of a tire on a heavy vehicle; and determining at least a portion of the one or more tire parameters based on the input data. The method further comprises the steps of: configuring a tire model, wherein the tire model defines a relationship between wheel slip and generated wheel force, and wherein the tire model is parameterized by one or more tire parameters; and controlling movement of the heavy vehicle based on a relationship between the wheel slip and the generated wheel force. In this way, vehicle control may be based on an accurate and up-to-date tire model that better reflects the current properties of the tire. This type of wheel slip based vehicle control has proven to provide superior performance compared to, for example, conventional torque based control strategies, and is further improved by the dynamically adapted tire model disclosed herein.

According to aspects, the input data comprises input data from one or more sensors arranged to measure one or more operating parameters of the tyre. The sensor may be configured to provide real-time data from the tire, thus enabling real-time dynamic adaptation of the tire model to quickly react to changes in the tire properties. Therefore, if the tire properties change, the tire model will also change, which is an advantage.

According to aspects, the one or more operating parameters include any of the following: vehicle speed, wheel rotational speed, tire pressure, tire temperature, tire acceleration, tire strain, tire GPS location, weather, ambient temperature, rain classification data, normal load, slip angle, steering angle, and applied torque. It is therefore an advantage that the tire model can be adapted to many different operating parameters.

According to aspects, the input data includes data relating to the tire design obtained from a memory. Different types of tires may have different properties and may react differently to events such as low road friction, high temperature, rain, etc. By taking into account the tire design, the model may be made more accurate. The data related to the tire design may include, for example, any of the following: tire nominal size, tire structural characteristics, tire chemical composition, and tire history.

According to aspects, the one or more estimated tire parameters include any of the following: tire wear, tire longitudinal stiffness, tire lateral stiffness, tire rolling resistance, tire peak friction, tire rolling radius, tire ground contact surface properties, tire balance properties, and wheel alignment properties. An advantage is that all these different tire parameters can be captured by the tire model. Having accurate information about one or more of these parameters facilitates efficient and/or safe vehicle control.

According to aspects, the method includes iteratively updating at least a portion of one or more tire parameters based on the updated input data. Thus, the tire model is kept up to date despite, for example, changes in operating conditions and tire conditions.

According to aspects, a tire model is configured to define a relationship between wheel slip and generated wheel forces in a longitudinal direction and a lateral direction. By not only considering longitudinal slip, more advanced vehicle motion management is achieved.

According to aspects, a tire model is configured to model rolling resistance of a tire. By modeling the rolling resistance according to one or more of the tire properties, vehicle control may also be optimized with respect to rolling resistance, which is an advantage. For example, a control strategy for accomplishing the maneuver associated with the lower rolling resistance may be selected instead of the control strategy associated with the higher rolling resistance. Thus, according to aspects, the method further includes coordinating one or more motion support devices of the heavy vehicle to reduce tire rolling resistance under constraints including meeting the motion request. According to other aspects, the method further includes coordinating one or more motion support devices of the heavy vehicle to increase the mileage capability of the heavy vehicle.

According to aspects, a tire model is configured to model a wear rate of a tire. By modeling wear rate also in accordance with tire parameters, the vehicle control function may be configured to optimize vehicle control so that the tire is more durable. For example, vehicle control may be performed with the aim of minimizing or at least reducing tire wear. Thus, according to aspects, the method further includes coordinating one or more motion support devices of the heavy vehicle to reduce the tire wear rate under constraints including meeting the motion request.

According to aspects, a tire model is configured to define a relationship between wheel slip and both propulsion and braking wheel forces. Thus, the tire model disclosed herein may support both acceleration and braking operations, which is an advantage.

According to aspects, a tire model is configured to model a self-aligning torque of a tire. It is an advantage to have a good understanding of the self-aligning torque characteristics of the tire, as this simplifies vehicle control by eliminating some of the behavioral uncertainties that might otherwise lead to control inaccuracy.

According to aspects, the method includes coordinating one or more motion support devices of the heavy vehicle to reduce a stopping distance of the heavy vehicle. Thus, by predicting the braking force to be generated by a particular control action, the tire model disclosed herein may be used to more efficiently apply braking. For example, some tires may be able to withstand greater braking forces than other tires. More braking force can be allocated to these tires than to other tires that cannot support a larger braking force due to wear caused by, for example, aging effects or the like.

Also disclosed herein are control units, computer programs, computer readable media, computer program products and vehicles associated with the advantages discussed above.

In general, all terms used in the claims should be interpreted according to their ordinary meaning in the technical field, unless explicitly defined otherwise herein. All references to "a/an/the element, device, component, means, step, etc" are to be interpreted openly as referring to at least one instance of the element, device, component, means, step, etc., unless explicitly stated otherwise. The steps of any method disclosed herein do not have to be performed in the exact order disclosed, unless explicitly stated. Further features of, and advantages with, the present invention will become apparent when studying the appended claims and the following description. Those skilled in the art realize that different features of the present invention can be combined to create embodiments other than those described in the following without departing from the scope of the present invention.

Drawings

The following is a more detailed description of embodiments of the invention, cited as examples, with reference to the accompanying drawings. In the drawings:

FIG. 1 schematically illustrates a vehicle for cargo transportation;

FIG. 2 is a graph showing an example of a tire model;

fig. 3 is a block diagram showing control of the motion support apparatus;

FIG. 4 illustrates a control architecture for controlling a vehicle;

FIG. 5 illustrates an example vehicle motion support device control system;

FIGS. 6A-6C are flowcharts illustrating example methods;

fig. 7 schematically shows a sensor unit and/or a control unit; and is also provided with

FIG. 8 illustrates an example computer program product.

Detailed Description

The present invention now will be described more fully hereinafter with reference to the accompanying drawings, in which certain aspects of the invention are shown. This invention may, however, be embodied in many different forms and should not be construed as limited to the embodiments and aspects set forth herein; rather, these embodiments are provided by way of example so that this disclosure will be thorough and complete, and will fully convey the scope of the invention to those skilled in the art. Like reference numerals refer to like elements throughout the specification.

It is to be understood that the invention is not limited to the embodiments described herein and shown in the drawings; rather, one of ordinary skill in the art will recognize that many variations and modifications may be made within the scope of the appended claims.

Fig. 1 shows a heavy vehicle 100. This particular example includes a tractor unit 110 arranged to tow a trailer unit 120. The tractor 110 includes a Vehicle Control Unit (VCU) 130 arranged to control various functions of the vehicle 100. For example, the VCU may be arranged to perform Vehicle Motion Management (VMM) functions including controlling wheel slip, vehicle unit stability, and the like. The trailer unit 120 optionally also includes a VCU 140, which then controls one or more functions on the trailer 120. The VCU or VCUs may be communicatively coupled to the remote server 150, for example, via a wireless link. The remote server may be arranged to perform various configurations of the ECU and provide various forms of data to the ECU 130, such as providing data regarding the brand and type of tires mounted on the vehicle 100, as will be discussed in more detail below.

Of course, the vehicle combination 100 may also include additional vehicle units, such as one or more cart units and more than one trailer unit.

The vehicle 100 is supported by wheels, wherein each wheel includes a tire. Tractor unit 110 has normally steered front wheels 160 and rear wheels 170, at least one pair of which are driven wheels. Typically, the rear wheels of the tractor 110 may be mounted on a support axle or a push axle. The trailing axle (tag axle) is where the rearmost drive axle is unpowered, also known as the free rolling axle or the stationary axle. The push axle (pusher axle) is where the forward most drive axle is not powered. The trailer unit 120 is supported on trailer wheels 180. Trailers with driven wheels and even steering axles are also possible.

One or more of the rear axles and/or one of the axles on the trailer 120 may be a liftable axle. A lift axle (also known as a telescopic axle) is an axle that can be lifted such that its tires do not contact the road surface. This improves fuel economy and reduces maintenance and tire wear. It may also reduce or increase the dynamic stability characteristics of the vehicle, and it may increase or decrease road wear, depending on the vehicle load, which axles are lifted, and the driving situation in which the axles are lifted.

One of the rear axles and/or one of the axles on the trailer 120 may be a liftable axle. A lift axle (also known as a telescopic axle) is an axle that can be lifted such that its tires do not contact the road surface. This improves fuel economy and reduces maintenance and tire wear, but it increases road wear. One or more of the wheels may also be mounted with an active suspension that may be controlled by the VCUs 130, 140, for example, to adjust the normal force of one or more tires.

Tires on wheels play a significant role in determining the performance and capabilities of the vehicle 100. A well-designed set of tires will provide good traction and fuel economy, while a poorly designed set of tires or excessively worn tires may reduce traction and fuel economy and may even result in unstable vehicle combinations, which is of course undesirable.

The present disclosure relates to a software tire model that models tire parameters and tire behavior, for example, for a given vehicle state (such as vehicle speed, normal load, etc.). The tire model may be fully utilized by the VCU to optimize control of the vehicle 100. For example, the tire models disclosed herein may be used to model a relationship between generated wheel force and wheel slip, which then allows the VCU to better control the vehicle by requesting wheel slip from the torque-generating device rather than directly requesting torque. Because the higher bandwidth control loop is operating locally (i.e., closer to the wheel end), the torque-generative devices can then maintain the generated wheel forces more stable. Some example tire models may also be used to estimate tire wear rates based on vehicle conditions, i.e., whether a particular vehicle maneuver or operation may result in excessive tire wear. Further, other tire models discussed herein model tire rolling resistance such that the VCU may optimize vehicle control to reduce tire rolling resistance and thus improve energy efficiency for a particular transportation mission or for only a single maneuver. The tire models discussed herein are configured to be dynamically updated as the vehicle is operated. Thus, it is preferred that the tire model is dynamic rather than static, which means that the tire model will be able to model the tire parameters better and more closely as a function of, for example, the overall driving scenario and the state of the tire over time, as the tire characteristics will change due to wear and changes in inflation pressure and temperature.

Some important properties and characteristic parameters of the tire will now be discussed. These tire parameters are optionally included in the tire model as tire parameters from which the VCU 130, 140 may determine other performance and characteristics of the tire, or simply as tire characteristics that may be used more or less directly by the VCU 130, 140 to optimize various control decisions.

Tires that rotate at high speeds tend to develop larger diameters, i.e., larger rolling radii, due to centrifugal forces forcing the tread rubber away from the axis of rotation. This effect is commonly referred to as centrifugal growth. As the tire diameter increases, the tire width decreases. Excessive centrifugal growth may significantly affect the behavior of the tire.

Pneumatic grip of a tire refers to the effect of a similar grip produced by an elastomeric tire rolling on a hard surface and subjected to side loads (such as in cornering). The pneumatic trailing distance parameter of a tire describes the distance of the resultant force at which tire sideslip occurs behind the geometric center of the ground contact surface of the tire.

The slip angle or sideslip angle (denoted herein as α) is the angle between the actual direction of travel of the rolling wheel and the direction in which it is pointing (i.e., the angle of the vector sum of the wheel translational speeds).

The relaxed length of the tire is a characteristic of the pneumatic tire that describes the delay from when the slip angle is introduced to when the cornering force reaches a steady state value. Typically, the relaxed length is defined as the rolling distance required for the tire to reach 63% of steady state lateral force, although other definitions are possible.

The vertical stiffness or spring rate is the ratio of the tire vertical force to vertical deflection and it contributes to the overall suspension performance of the vehicle. In general, the spring rate increases with inflation pressure.

The ground contact surface or footprint of a tire is the area of the tread that is in contact with the road surface. This region transmits forces between the tire and the road via friction. The aspect ratio of the ground plane may affect steering and cornering behaviour. The tire tread and sidewall elements experience deformation and recovery as they enter and leave the footprint. Since rubber is an elastomer, it will deform during this cycle. As the rubber deforms and recovers, it applies a cyclical force to the vehicle. These variations are collectively referred to as tire uniformity. Tire uniformity is characterized by Radial Force Variation (RFV), lateral Force Variation (LFV), and tangential force variation. The force varying machine measures radial force variation and lateral force variation at the end of the manufacturing process. Tires that exceed the specified limits of RFV and LFV may be rejected. Geometric parameters (including radial runout, lateral runout, and sidewall bulge) are measured as quality checks at the tire factory using a tire uniformity machine at the end of the manufacturing process.

The cornering or lateral forces of a tire are the lateral (i.e. parallel to the road surface) forces that are generated by the vehicle tire when cornering.

The rolling resistance is the resistance to rolling caused by deformation of the tire in contact with the road surface. As the tire rolls, the tread enters the contact area and deforms flat to conform to the road. The energy required to perform the deformation depends on the inflation pressure, the rotational speed, and many physical properties of the tire structure, such as spring force and stiffness. In trucks where rolling resistance is a very high proportion of fuel consumption, tire manufacturers often seek lower rolling resistance tire constructions to improve fuel economy.

Ride comfort is related to the overall experience of the driver or passenger while riding the vehicle. Ride comfort depends on the behavior of the vehicle, which in turn depends on the nature of the tires.

Self-aligning torque (SAT) refers to the torque produced by a tire when rolling, which tends to steer the tire, i.e., rotate it about a vertical axis.

Tire models may be used to describe the properties of a particular tire, such as those described above, as well as other properties. For example, a tire model may be used to define the relationship between the longitudinal tire force Fx of a given wheel and the equivalent longitudinal wheel slip of that wheel. Longitudinal wheel slip lambda _x Involves the difference between the rotational speed of the wheel and the ground speed, and willAs discussed in more detail below. The wheel rotation speed ω is a rotation speed of the wheel given in units of, for example, revolutions per minute (rpm) or angular speed according to radian/sec (rad/sec) or degree/sec (deg/sec). The variation of wheel behaviour with wheel slip with respect to wheel forces generated in the longitudinal direction (rolling direction) and/or the transverse direction (orthogonal to the longitudinal direction) is discussed in Hans panejka, "Tyre and vehicledynamics" (Elsevier ltd.2012, ISBN 978-0-08-097016-5). See, for example, chapter 7, wherein the relationship between wheel slip and longitudinal force is discussed.

Longitudinal wheel slip lambda according to SAE J670 (SAE vehicle dynamics Commission, 24 th month of 2008) _x Can be defined as

Where R is the effective wheel radius in meters, ω _x Is the angular velocity of the wheel, and v _x Is the longitudinal speed of the wheel (in the coordinate system of the wheel). Thus lambda is _x Between-1 and 1, and quantifying the degree of wheel slip relative to the road surface. Wheel slip is essentially the difference in speed measured between the wheel and the vehicle. Thus, the techniques disclosed herein may be applicable to any type of wheel slip definition. It should also be appreciated that in the coordinate system of the wheels, the wheel slip value corresponds to the wheel speed value given the speed of the wheel on the road surface.

The lateral slip of a tire is the angle between the direction of movement of the tire and the direction in which the tire is pointing. Lateral slip may occur, for example, in cornering and be caused by deformations of the tire structure and tread. Despite the name, for smaller slip angles, no actual slip is required. Lateral wheel slip is generally defined as

Wherein v is _x Is the longitudinal velocity component of the wheel movement, andand v _y Is the lateral velocity component of the wheel motion. Lateral tire slip is discussed in detail in, for example, "Tyre and vehicledynamics" by Hans Pacejka (Elsevier Ltd.2012, ISBN 978-0-08-097016-5).

Transverse wheel slip lambda _y Can optionally also be defined as

Wherein v is _y Is at a velocity v with respect to the longitudinal direction _x The lateral velocity of the wheel (in the coordinate system of the wheel) measured in the direction orthogonal to the direction of (a) the wheel.

In order for the wheel (or tire) to generate wheel forces, slip must occur. For smaller slip values, the relationship between slip and generated force is approximately linear, with the proportionality constant typically expressed as the slip stiffness of the tire. Referring to fig. 2, a tire 230 (such as any of tires 160, 170, 180) is subjected to a longitudinal force F _x Transverse force F _y And normal force F _z . Normal force F _z Is a key to determining some important vehicle properties. For example, the normal force determines to a large extent the longitudinal tire force F achievable by the wheel _x Because in general F _x ≤μF _z Where μ is the coefficient of friction associated with the road friction condition. The maximum available lateral force for a given lateral slip can be described by the so-called magic formula as described in HansPacejka, "Tyre and vehicle dynamics" (Elsevier ltd.2012, ISBN 978-0-08-097016-5).

FIG. 2 shows a tire force F that is exhibited to be attainable _x 、F _y Graph 200 of an example of variation with wheel slip. The longitudinal tire force Fx shows a portion 210 that increases almost linearly with small wheel slip, followed by a portion 220 that has more non-linear behavior with larger wheel slip. The obtainable lateral tire force Fy decreases rapidly even at relatively small longitudinal wheel slip. It is desirable to maintain vehicle operation in linear region 210, wherein the longitudinal force available in response to an applied braking command is more easily predicted, and wherein ifIf desired, sufficient lateral tire forces may be generated. To ensure operation in this region, a wheel slip limit λ of approximately, for example, 0.1 may be applied to a given wheel _LIM . For greater wheel slip, for example, over 0.1, a more non-linear region 220 is obtained.

For both longitudinal and transverse tire forces, wheel forces in the linear region can be described in terms of stiffness, i.e.,

F _x ＝C _x (w,F _z )λ _x

F _y ＝C _y (w,F _z )α

where w is a parameter indicative of tire wear, α is the slip angle of the tire, and C _x And C _y Is a stiffness function. Tire stiffness C _x And C _y Generally with wear w and normal force F _z And increases. Both of the above functions represent tire models that depend on tire parameters and vehicle state properties. Given a tire model, e.g. function C _x (·)λ _x And/or function C _y (. Cndot.) alpha and tire parameters w, F _z With respect to the input data, it is possible for the VCU to obtain an accurate relationship between the generated wheel force and the wheel slip. The relationship will vary depending on the tire parameters, i.e. the relationship is between tire wear and normal force F of the tire over time _z Dynamic relationships updated upon change.

Such a tire model may be determined by actual experimentation, analytical derivation, computer modeling, or a combination of the foregoing. In practice, the tire model may be represented by a look-up table (LUT) indexed by tire parameters, or as a set of coefficients describing a polynomial or the like. Wherein the set of coefficients is selected based on tire parameters, and wherein the polynomial describes a relationship between tire behavior and vehicle state.

Instead or in addition, other tire models of interest may model the tire wear rate based on, for example, vehicle speed and normal load, and/or model the tire rolling resistance for a given vehicle condition, which is dependent on the particular tire parameters of the tire currently mounted on a given wheel.

Fig. 3 schematically illustrates functionality 300 for controlling wheels 330 through some example MSDs, here including friction brakes 320 (such as disc brakes or drum brakes) and propulsion devices 310 (such as electric motors or combustion engines). The friction brake 320 and the propulsion device 310 are examples of wheel torque generating devices, which may also be referred to as actuators and may be controlled by one or more motion support device control units 340. The control is based on, for example, measurement data obtained from the wheel rotation speed sensor 350 and from other vehicle state sensors such as radar sensors, lidar sensors, and vision-based sensors (such as camera sensors and infrared detectors). Other example torque-generative motion support devices that may be controlled in accordance with the principles discussed herein include engine retarders and power steering devices. The MSD control unit 340 may be arranged to control one or more actuators. For example, it is not uncommon for the MSD control unit to be arranged to control the MSD for both wheels of the axle. By using, for example, a global positioning system, vision-based sensors, wheel rotational speed sensors, radar sensors, and/or lidar sensors to estimate vehicle unit motion and translate that vehicle unit motion into a local coordinate system of a given wheel (in terms of, for example, longitudinal and lateral velocity components), it is possible to accurately estimate wheel slip in real-time by comparing vehicle unit motion in a wheel reference coordinate system to data obtained from wheel rotational speed sensors 350 arranged in conjunction with the wheel.

Both the friction brake 320 and the propulsion device interact with the road surface via wheels 330 comprising tires. Thus, tire properties and behavioral characteristics can affect how the various control actions of friction brake 320 and propulsion device 310 produce vehicle motion. Included in the system is a software-based tire model 380. The tire model provides information about the tire currently mounted on the wheel 330, its properties, and behavioral characteristics. VMM 360 and/or MSD control unit 340 use the information provided by the tire model to predict the consequences of different control allocations. This means that the VMM and/or the MSD control unit may optimize the control actions according to the specific characteristics and properties of the tire.

According to a first example, VMM 360 uses input from a tire model to predict the generated wheel forces from wheel slip. The predictive function (i.e., the mapping between slip and force) is determined by current tire parameters such as tire slip stiffness properties, tire thread area temperature, tire nominal inflation pressure, current tire normal force, wheel rotational speed, tire wear, and road friction coefficient.

According to a second example, the tire model is configured to predict a tire wear rate (in g/km or g/s) of the tire for an upcoming maneuver, wherein the mapping between the tire wear rate and the vehicle state is also determined by the current tire parameters. This allows VMM function 360 to select between different control options, all of which achieve the desired global force generation, but may be associated with significantly different tire wear rates.

According to a third example, the tire model is configured to predict tire rolling resistance of the tire for an upcoming maneuver, vehicle state, and vehicle configuration. This allows VMM function 360 to select between different control options and vehicle configurations, both of which achieve the desired global force generation, but which may be associated with significantly different tire rolling resistances. Thus, the VMM function may, for example, decide that it is beneficial for both rolling resistance and tire wear rate if the lift axle is lifted from the ground in a given driving scenario.

According to a fourth example, the tire model is configured to predict a ride comfort index of the vehicle for an upcoming maneuver based on the response and behavior of the tire during the maneuver as predicted by the tire model. This also allows the VMM function 360 to choose between different control options and strategies to accomplish maneuvers in a safe and efficient manner while a secondary purpose is to reflect ride comfort. Thus, VMM function 360 may control the vehicle to operate with greater ride comfort than previous vehicles.

As described above, the tire model may be implemented as a look-up table or other type of function. The tire model is parameterized, i.e., defined, by one or more tire parameters. This means that the function itself varies according to the nature of the tyre. As illustrated above, the tire model may be used to model various relationships, such as a relationship or map between wheel slip and generated wheel force, and/or a map between tire wear rate and vehicle conditions (such as tire normal load, vehicle speed, and wheel slip). It should be understood that the present disclosure is not limited to any particular form of tire model structure. Rather, it should be appreciated that many different types of mathematical and/or experimental-based functions and mappings may be used as the tire model.

Referring also to fig. 4 and 5, the traffic condition management (TSM) function 370 plans to perform driving operations in a time range of, for example, around 1 to 10 seconds. This time range corresponds to, for example, the time it takes the vehicle 100 to pass through a curve. The vehicle maneuvers planned and performed by the TSM may be associated with acceleration curves and curvature curves that describe the desired vehicle speed and cornering for a given maneuver. The TSM continually requests the desired acceleration profile a from VMM function 360 _req And curvature curve c _req The VMM function performs force distribution to satisfy requests from the TSM in a secure and robust manner. The TSM function 370 may also determine vehicle maneuvers based on the tire model 380, as indicated in fig. 3. For example, TSM function 370 may compare two or more different maneuvers that achieve the same goal in terms of, for example, tire wear and/or rolling resistance, and then select the most advantageous one in these respects.

The desired acceleration and curvature curves may optionally be determined based on driver input through a human-machine interface 440 of the heavy vehicle via normal control input devices such as steering wheel, accelerator pedal, and brake pedal, although the techniques disclosed herein are equally applicable to autonomous or semi-autonomous vehicles. The exact method for determining the acceleration and curvature curves is not within the scope of the present disclosure and will therefore not be discussed in detail herein. It should be noted that the traffic condition management and/or transportation mission and route planning function 420 may configure various properties of the vehicle, such as raising and lowering the lift axle, adjusting the suspension, and the like.

Sensors arranged to provide information about the vehicle environment 430 provide input to the overall control stack 400, and optionally also include connections to remote processing resources (such as cloud-based processing resources 410) in the control stack. The remote server 150 in fig. 1 may be included in this type of cloud layer 410.

VMM function 360 operates in a time range of about 0.1 to 1.5 seconds or so and continuously curves acceleration a _req And curvature curve c _req Is converted into control commands for controlling vehicle motion functions actuated by different MSDs of the vehicle 100, which report back to the VMM capabilities which in turn serve as constraints in vehicle control. The accuracy of such control is enhanced by the advanced tire model 380 discussed herein.

Referring primarily to fig. 5, the VMM function 360 performs vehicle state or motion estimation 520, i.e., the VMM function 360 continuously determines a vehicle state s (typically vector variables) including position, speed, acceleration, yaw motion, normal force, and articulation angle of the different units in the vehicle combination by monitoring the vehicle state and behavior using various sensors 510 disposed on the vehicle 100 that are typically, but not always, associated with the MSD.

The result of the motion estimation 520 (i.e., the estimated vehicle state s) is input to a global force generation module 530 that determines the required global force that needs to be generated on the vehicle unit to satisfy the motion request from the TSM 370. The MSD coordination function 540 distributes, for example, wheel forces and coordinates other MSDs, such as steering devices and suspensions. The coordinated MSDs then together provide the desired lateral and longitudinal forces Fy and Fx and the required moment Mz on the vehicle unit to achieve the desired movement of the vehicle combination 100. As indicated in FIG. 5, the MSD coordination function 540 may slip the wheels by λ _i Wheel rotation speed ω, torque T _i And/or steering angle delta _I Any of which is input to a different MSD.

The MSD coordination function 540 is supported by a tire model function 380 that continually updates the software-based model of the tire on the vehicle. The MSD coordination function 540 may determine a relationship between wheel slip and generated wheel forces, for example, using a tire model, as discussed in connection with FIG. 2. Further, according to another example, the MSD coordination function may decide to fully satisfy some different control options and/or different MSD coordination solutions from the current request of the TSM 370, and thereby also improve some secondary objectives, such as reducing tire wear rate and/or improving energy efficiency of transportation tasks by reducing rolling resistance. Such selection and/or optimization may be performed by the optimization module 550. In other words, it should be appreciated that additional degrees of freedom are typically available when performing MSD coordination, meaning that a given set of global forces are typically available in many different ways. Each such MSD coordination solution may be evaluated based on the tire model 380, such that preferences for a particular solution that provides reduced tire wear and/or reduced rolling resistance may be generated.

The tire model is parameterized by one or more tire parameters such as tire wear, tire normal load, tire slip stiffness, etc. These tire parameters may of course be preconfigured. However, additional advantages may be obtained if the tire parameters are estimated or otherwise determined based on the tire data obtained from the memory 565 or based on the tire data obtained from the one or more sensors 510. Tire parameters may be estimated or at least periodically updated by a tire parameter estimation software (TYPRESSW) module 560.

In general, the vehicle control methods and various example tire models 380 disclosed herein may be based on input signals, including tire-based sensors (such as pressure sensors, thread wear sensors, temperature sensors, vibration sensors, rim-based sensors, etc.). The input signals may also include data obtained from other sensors disposed on the vehicle 100, such as wheel rotation speed sensors, radar sensors, lidar sensors, vibration sensors, acoustic sensors, and the like. The methods and tire models disclosed herein may also obtain and use information received from a remote device (such as remote server 150) via a wireless link, as well as driver requests and various actuator states.

Inputs to TYPRESSW module 560 and optional tire model 380 may include wheel speed v relative to the road surface _x Wheel rotation speed omega _x Tire acceleration, tire pressure, tire temperature, tire strain, tire GPS location and weather data, ambient, rain classification (obtained from a rain sensor and/or wiper speed, etc.), normal load F _z Slip angle alpha and/or steering angle delta and applied torque (propulsion torque and/or braking torque).

Accordingly, it should be appreciated that a vehicle control unit (such as VCU 130, 140) may be arranged to store the tire model 380 in memory, for example, as a look-up table or mathematical function. The tyre model is arranged to be stored in the memory in dependence on the current operating conditions and parameters of the tyre. This means that the tire model can be advantageously adapted to the operating conditions and overall state of the tire, which means that a more accurate model is obtained than a model that does not take into account the details of the tire. The model stored in the memory may be determined analytically or experimentally based on the structural design details and chemical composition of the tire mounted on the wheel. Additionally, the control unit may be configured to access a set of different models selected based on the current tire operating conditions. One tire model may be tailored for high load driving with higher normal forces, another tire model may be tailored for easy-to-track conditions with lower road friction, and so on. The selection of the model to be used may be based on a set of predetermined selection rules.

Thus, the model may be configured to take as input parameters, for example, normal force or road friction, whereby the tire model is obtained from the current operating conditions of the wheel. It should be appreciated that many aspects of the operating conditions may be approximated by default operating condition parameters, while other aspects of the operating conditions may be roughly divided into a smaller number of categories. Thus, obtaining a tire model from the current operating conditions of the wheel does not necessarily mean that a large number of different models need to be stored, or that complex analytical functions of operating condition variations can be taken into account with fine granularity. Instead, it may be sufficient to select two or three different models depending on the operating conditions. For example, one model is used when the vehicle is heavily loaded, and another model is used otherwise. In all cases, the mapping between tire force and wheel slip is changed in some way depending on the operating conditions, thereby improving the accuracy of the mapping.

The tire model may also be implemented at least in part as an adaptive model configured to automatically or at least semi-automatically adapt to the current operating conditions of the vehicle. This may be accomplished by constantly monitoring the response of a given wheel in terms of the wheel forces generated in response to a given wheel slip request and/or monitoring the response of the vehicle 100 in response to a wheel slip request. The adaptive model may then be adjusted to more accurately model the wheel forces obtained in response to a given wheel slip request from the wheel.

The outputs of the tire model 380 can optionally be grouped into two categories: current state estimation and model parameters. The current state estimate represents an estimate of the instantaneous tire and wheel states. Based on the shared generic tire model definition, the model parameters are a set of signals that encompass the current estimated tire model "coefficients". The tire model (or models) may be used by the VCUs 130, 140 to predict what forces, rolling radii, rolling resistance, and wear rates may be expected, for example, under current tire conditions and vehicle motion characteristics.

The tire model may be adapted to model a number of tire parameters, individually or in combination, and to model capabilities in accordance with tire design, tire condition, and vehicle motion conditions:

[F _x,stat ,F _y,stat ]＝f1(C _x0 ,C _y0 ,T _s0 ,P ₀ ,F _z0 ,v _x0 ,T _s ,P,F _z ,v _x ,w,λ _x ,λ _y /α,μ,s _c ),

[σ _x ,σ _y ]＝f2(σ _x0 ,σ _y0 ,T _s0 ,P ₀ ,F _z0 ,v _x0 ,T _s ,P,F _z ,w,λ _x ,λ _y /α,μ,s _c ),

R＝f3(R ₀ ,T _s0 ,P ₀ ,F _z0 ,v _x0 ,T _s ,P,F _z ,v _x ,w),

M _rr ＝f4(T _s0 ,P ₀ ,F _z0 ,v _x0 ,X _M ,T _s ,P,F _z ,v _x ,w,λ _x ,λ _y /α,μ,s _c ),

where f1 to f5 are functions, which may be analytical functions, numerical approximations or simply look-up tables. In the above-mentioned equation(s),

Fx _,stat 、Fy _,stat calculated steady-state forces in the long and lateral directions respectively,

σ _x 、σ _y the instantaneous relaxed lengths in the longitudinal and transverse directions respectively,

C _x0、 C _y0 is the longitudinal and transverse slip stiffness of the tire in nominal condition,

σ _x,0 、σ _y,0 is the longitudinal and transverse relaxed length in nominal condition,

_Ts,0 is the instantaneous structural tire tread area temperature,

_Ts is the nominal structural tire tread area temperature,

P is the instantaneous inflation pressure and,

P ₀ is the nominal inflation pressure of the gas to be inflated,

F _z is the instantaneous vertical load that is applied to the load,

F _z,0 is the nominal vertical load that is to be applied,

v _x is the actual longitudinal speed of the tyre (on the ground),

v _x,0 is the nominal longitudinal velocity of the vehicle,

w is the wear (0 to 100%), 0% corresponds to an entirely new condition,

λ _x 、λ _y is the value of the instantaneous slip and,

μ is the instantaneous friction force estimate,

s _c is a transient discrete state surface condition,

r is the calculated instantaneous (free) rolling radius,

R ₀ is the (free) rolling radius at nominal conditions,

M _rr is a torque calculated from rolling resistance, and

is the wear rate of the tire (in g/km or g/s).

It should be appreciated that the equation may also be restated according to different definitions of lateral slip, e.g., α or λ as discussed above _y 。

Dynamic (transient) forces can also be deduced. At least two alternatives are possible: relaxing the calculated static force, or by incorporating lambda in the above formula _x 、λ _y Replaced by lambda _x-dyn 、λ _y-dyn To calculate a slip angle (s _i,dyn ) And applying a static force formula.

/>

Where i is x or y, i.e., the longitudinal direction or the transverse direction.

Fig. 6A-6C are flowcharts outlining and illustrating the discussion above. These methods may be performed by the VCUs 130, 140 in the vehicle 100, or at least partially by the remote server 150. Such VCUs may be implemented in a central processing unit or distributed among multiple units.

Referring also to fig. 5, fig. 6A illustrates a method for controlling the movement of the heavy vehicle 100. The method includes obtaining input data 561, 562 of Sa1 relating to one or more parameters of the tires 150, 160, 170 on the heavy vehicle 100. The input data Sa12 optionally includes data related to the tire design obtained from the storage 565. The input data may include configuration data 562 related to, for example, the tire brand and/or model, the chemical composition of the tire, the nominal size of the tire, or other structural and mechanical characteristics and features of the tire. Optionally, the data related to the tire design also includes a tire history indicating whether the tire has undergone any process or event that may have changed the behavior of the tire. For example, the tire may have been subjected to retreading and/or may have been serviced in a manner that may affect its behavioral characteristics. The input data may also include data 561 from one or more sensors 510, two sensors arranged in relation to the actual tire, and/or sensors arranged on the vehicle 100. These optional sensors 510 are arranged to measure one or more operating parameters of the tire, wherein the one or more operating parameters may include any of the following: vehicle speed, wheel rotational speed, tire pressure, tire temperature, tire acceleration, tire strain, tire GPS location, weather, ambient temperature, rain classification data, normal load, slip angle, steering angle, and positive/negative torque applied to the tire.

The method further includes determining at least a portion of the one or more tire parameters of Sa2 based on the input data. Some of the parameters may be determined directly. For example, the nominal tire pressure may be given directly from a pressure sensor arranged to measure the tire pressure. Other parameters of the tire may be estimated based on the input data. For example, the effective tire rolling radius may be determined based on a combination of the tire nominal size, the tire pressure, and the tire rotational speed. Tire wear may be estimated by integrating the estimated tire wear rate or simply based on the age of the tire. The one or more estimated tire parameters Sa21 optionally include any of the following: tire wear, tire longitudinal stiffness, tire lateral stiffness, tire rolling resistance, tire peak friction, tire rolling radius, tire ground contact surface properties, tire balance properties, and wheel alignment properties.

A Sa3 tire model is then configured, wherein the tire model defines a relationship between wheel slip and generated wheel force, for example, as discussed above in connection with fig. 2. The tire model is then parameterized by one or more tire parameters. For example, as a simple example, a tire model may include only a linear approximation of the relationship between wheel slip and the generated force determined from the tire's slip stiffness parameters. As described above, one key concept of the techniques disclosed herein is that the Sa22 tire model and different estimated and measured tire parameters may be repeatedly updated based on updated input data. This means that as the tire progresses through its life cycle, the tire model and various tire parameters will remain updated from a new tire to a tire that is nearly worn out and needs replacement. Thus, the tire model will be more accurate than a fixedly configured tire model. In addition, the tire model will react to the misconfiguration and eliminate any differences between the preconfigured data and the actual behavior of the tire.

According to some aspects, the tire model Sa31 is configured to define a relationship between wheel slip and generated wheel forces in the longitudinal and lateral directions, as discussed above in connection with fig. 2. The VMM function of the vehicle 100 may advantageously use the tire model to perform MSD coordination to generate the desired global force distribution on different vehicle units of a heavy-duty articulated vehicle in a more accurate manner. For example, in the case of a desired acceleration, the VMM function may coordinate the MSD to produce wheel slip that collectively provide the desired force in the direction of the desired acceleration. The tire model Sa34 is optionally configured to define the relationship between wheel slip and propulsion and braking wheel forces, or to define only one of propulsion or braking.

According to other aspects, the tire model Sa32 is configured to model the rolling resistance of the tire. This means that the VMM functionality can compare different solutions to the MSD coordination problem in terms of rolling resistance and select a solution associated with less rolling resistance than other solutions to the MSD coordination problem. Furthermore, if vehicle 100 includes one or more lift axles, the VMM function may evaluate whether the lift axles would result in more advantageous operation in terms of rolling resistance. In this way, the VMM functionality may optimize or at least improve vehicle control in order to achieve lower rolling resistance. Thus, the method disclosed herein is strongly likely to provide reduced overall rolling resistance of the vehicle 100.

According to a further aspect, the tire model Sa33 is configured to model the wear rate of the tire, for example, according to the vehicle state and/or manoeuvre. Accordingly, various vehicle control functions may take into account the tire wear rate. This means that one or more viable schemes for generating a set of desired global forces through different MSDs can be discarded, as they can result in excessive tire wear rates. This may occur, for example, when the vehicle is turning, where some control allocations result in severe scratches. By incorporating tire models that include tire wear rates for different vehicle conditions and tire parameter outputs, tire life may be extended by avoiding vehicle maneuvers associated with high tire wear rates.

The tire model Sa35 may also be configured to model the self-aligning torque of the tire. This self-aligning torque is sometimes also part of the MSD coordination function. Thus, having a good understanding of this important force simplifies performing accurate vehicle motion management.

The method further includes controlling movement of the Sa4 heavy vehicle based on a relationship between wheel slip and the generated wheel force. Examples of control are discussed above in connection with, for example, fig. 3 and 4. For example, the method may include coordinating one or more motion support devices of the Sa41 heavy vehicle 100 to reduce the tire wear rate under constraints including meeting the motion request. This means that there are many possible solutions for the VMM function as to how to generate a desired set of global forces and moments acting on different vehicle units in the vehicle 100. Each solution can then be evaluated in terms of tire wear rate by the tire model, and one solution that does not result in excessive tire wear rate can be selected. This type of function may be used to constrain vehicle motion management to select only control solutions associated with limited tire wear rates. This function may also be used to provide a warning signal to the driver when the driver is performing vehicle control associated with a high tire wear rate. In this case, if the driver performs a manipulation harmful to the tire, a warning light or other notification means (such as an audible alarm signal) in the cabin may be triggered, and a message informing the driver of the high tire wear rate currently generated may be displayed.

The methods disclosed herein may also include coordinating one or more motion support devices of the Sa42 heavy vehicle 100 to reduce tire rolling resistance under constraints including meeting motion requests. Thus, in terms of tire wear rate, the VMM function may choose between different MSD coordinated solutions that all produce a desired set of global forces, and select a solution associated with acceptable or even minimal rolling resistance. Therefore, by selecting the control allocation associated with the reduced rolling resistance, the energy efficiency of the vehicle 100 is improved, which is an advantage.

According to some aspects, the tire model may be used to estimate or predict a stopping distance of the vehicle. Accordingly, the methods disclosed herein optionally include coordinating one or more motion support devices of the Sa43 heavy vehicle 100 to reduce the stopping distance of the heavy vehicle 100. Such coordination may include adjusting the lift axle, and/or creating a change in normal load by, for example, adjusting a suspension system, etc. This feature may be used to further optimize, for example, fuel economy or other forms of energy efficiency, thereby maintaining the stopping distance below a certain maximum value.

The methods disclosed herein may also include coordinating one or more motion support devices of the Sa44 heavy vehicle 100 to increase the mileage capability of the heavy vehicle 100.

It should be understood that many of the functions and features disclosed herein may be implemented independently of one another or in combination. In particular, features related to the tire wear rate estimation and the tire rolling resistance estimation may be implemented independently of features related to the tire force estimation, or in combination as a more advanced tire model capable of outputting more than one form of output data.

Fig. 6B is a flowchart illustrating a method for controlling the motion of the heavy vehicle 100 and in particular for estimating the wear rate of one or more tires on the vehicle from the vehicle motion state. Referring also to fig. 5, for example, the method includes obtaining input data 561, 562 of Sb1 related to one or more tire parameters of the tires 150, 160, 170 on the heavy vehicle 100. Tire parameters that may be relevant to determining wear rate may include, for example, tire chemistry and mechanical structure, ground contact surface geometry, inflation pressure, and the like. The method further includes estimating at least a portion of one or more tire parameters of Sb2 based on the input data. As described above, the input data may directly identify the tire parameters (e.g., chemical components that may be obtained from data stored in memory), or may be indirectly associated with the tire parameters. The sensor data may be used to estimate, for example, the current tire ground contact surface geometry.

In general, the one or more tire parameters may include any of tire pressure, tire temperature, tire strain, tire GPS location, weather, ambient temperature, and rain classification data. The data related to the tire design optionally includes any of a tire nominal size, tire structural characteristics, tire chemical composition, and tire history.

The method further includes configuring an Sb3 tire model, wherein the tire model defines a relationship between a tire wear rate and a vehicle motion state, and wherein the tire model is parameterized by one or more tire parameters. Thus, given a particular tire model structure, the tire model is first tuned to accommodate, i.e., parameterize, a given tire mounted to the vehicle. It should be appreciated that different tires on a vehicle may be associated with different tire model parameterizations, even though the tires mounted to different wheels of the vehicle are of the same brand and type, they may be subject to different operating conditions, and thus may have different tire model parameterizations. The tire model defines the relationship between the current or future vehicle motion state and the tire wear rate. This means that the tire model can be seen as a function or map between the vehicle motion state and the tire wear rate.

In general, the vehicle motion state may include any one of a vehicle speed, a wheel rotation speed, a tire acceleration, a tire normal load, a slip angle, a steering angle, and an applied torque. The vehicle motion state optionally further includes any one of a longitudinal wheel slip of the corresponding wheel of tire Sb31, a lateral wheel slip of the corresponding wheel of tire Sb32, a normal load of the corresponding wheel of tire Sb33, and a rotational speed of the corresponding wheel of tire Sb 34.

The method further includes estimating a vehicle motion state Sb4, and controlling Sb5 motion of the heavy vehicle based on the tire model and the vehicle motion state. Tire models may be used for various vehicle control functions. For example, if it is desired to reduce tire wear for a given vehicle, different control options or MSD coordination solutions may be compared in terms of tire wear rate, and a control option with an acceptable or even minimum tire wear rate may be selected. Vehicle configuration may also be determined with the aim of reducing the tire wear rate. For example, assume that the vehicle includes one or more lift axles or active suspension systems that allow the VCU to adjust the normal load on different axles or even on individual tires. In this case, a normal load distribution that results in reduced tire wear may be selected instead of a configuration that results in a higher degree of tire wear. Accordingly, tire wear of the vehicle 100 may be reduced, which is an advantage.

According to aspects, the one or more estimated tire parameters Sb21 include any one of the following: tire wear, tire longitudinal stiffness, tire lateral stiffness, tire rolling resistance, tire peak friction, tire rolling radius, tire ground contact surface properties, tire balance properties, and wheel alignment properties. These tire parameters may be used to "customize" a tire model to fit a given tire. Such a tire model will provide a more accurate mapping between vehicle operating conditions and tire wear rates than a more general tire model that is not tailored to accommodate a given tire. Advantageously, the tire model presented herein may be iteratively updated Sb22 for at least a portion of one or more tire parameters based on the input data. Thus, if the tire properties change over time, the model will also change in order to maintain an accurate mapping between vehicle operating conditions and tire wear rates.

There are many different examples as to how the vehicle control can be adjusted to take into account the tire wear rate, as given by the tire model in accordance with the vehicle operating conditions. The tire wear rate may be determined for both the current vehicle state, i.e., the extent to which the current vehicle state affects the tire in terms of tire wear, and predicted for future vehicle operation. For example, assume that the vehicle is about to turn and there are several different options at the time of the turn, namely steering by braking, steering by steering an axle, or a combination of both. The vehicle may also be able to select a path through a curve. The tire model may then be queried to determine tire wear associated with the different control options, and the option associated with the minimum tire wear rate may be selected. It will be appreciated that if the tire model is also configured to output data relating to, for example, rolling resistance, a combination of two selection criteria may be used in order to find a control option having a reasonable amount of tire wear while providing an acceptable degree of rolling resistance.

Advantageously, the wheel slip limit for vehicle motion control may be configured according to a predetermined acceptable target wear rate. Thus, tire wear may be significantly reduced by operating the vehicle at or below the preferred wheel slip limit as long as the vehicle is not experiencing a dangerous condition.

The method optionally further comprises any one of the following: the Sb51 wheel slip is controlled according to the wear rate corresponding to the vehicle motion state, the Sb52 normal load is controlled according to the wear rate corresponding to the vehicle motion state, for example, by adjusting the settings of the liftable axle of the vehicle according to the wear rate and/or the settings of the active suspension system. The method optionally further comprises any one of the following: controlling the bS53 wheel rotation speed according to the wear rate, controlling movement of the Sb54 heavy vehicle based on the configured target wear rate, and coordinating one or more movement support devices of the Sb55 heavy vehicle 100 to reduce the tire wear rate under constraints including meeting movement requests.

Vehicle control may also be performed at maximum or at least preferred stopping distance requirements, i.e. it may be required that the vehicle is able to stop completely within a specified distance. In this case, the method may include coordinating one or more motion support devices of the Sb56 heavy vehicle 100 to reduce the stopping distance of the heavy vehicle 100.

Fig. 6C is a flowchart illustrating a method for controlling the motion of the heavy vehicle 100 and in particular for estimating the rolling resistance of one or more tires on the vehicle from the vehicle motion state. Referring also to fig. 5, for example, the method includes obtaining input data 561, 562 of Sc1 related to one or more tire parameters of the tires 150, 160, 170 on the heavy vehicle 100. Tire parameters that may be relevant to determining rolling resistance may include, for example, tire chemistry and mechanical structure, ground contact surface geometry, inflation pressure, and the like. The method further includes estimating at least a portion of the Sc2 one or more tire parameters based on the input data. As described above, the input data may directly identify the tire parameters (e.g., chemical components that may be obtained from data stored in memory), or may be indirectly associated with the tire parameters. The sensor data may be used to estimate, for example, current tire ground contact surface geometry, current inflation pressure, and the like.

In general, the one or more tire parameters may include any of tire pressure, tire temperature, tire strain, tire GPS location, weather, ambient temperature, and rain classification data.

The data related to the tire design optionally includes any of a tire nominal size, tire structural characteristics, tire chemical composition, and tire history.

The method further includes configuring a Sc3 tire model, wherein the tire model defines a relationship between tire rolling resistance and vehicle motion state, and wherein the tire model is parameterized by one or more tire parameters. Thus, given a particular tire model structure, the tire model is first tuned to accommodate, i.e., parameterize, a given tire mounted to the vehicle. It should be appreciated that different tires on a vehicle may be associated with different tire model parameterizations, even though the tires mounted to different wheels of the vehicle are of the same brand and type, they may be subject to different operating conditions, and thus may have different tire model parameterizations. The tire model defines the relationship between the current or future vehicle motion state and the tire rolling resistance. This means that the tire model can be regarded as a function or map between the vehicle motion state and the tire rolling resistance.

In general, the vehicle motion state may include any one of a vehicle speed, a wheel rotation speed, a tire acceleration, a tire normal load, a slip angle, a steering angle, and an applied torque.

The vehicle motion state optionally further includes any one of a longitudinal wheel slip of the corresponding wheel of the tire Sc31, a lateral wheel slip of the corresponding wheel of the tire Sc32, a normal load of the corresponding wheel of the tire Sc33, and a rotational speed of the corresponding wheel of the tire Sc 34.

The method further includes estimating a vehicle motion state Sc4, and controlling Sc5 motion of the heavy vehicle based on the tire model and the vehicle motion state. Tire models may be used for various vehicle control functions. For example, if it is desired to reduce tire wear for a given vehicle, different control options or MSD coordination solutions may be compared in terms of tire rolling resistance, and a control option with acceptable or even minimal tire rolling resistance may be selected. Vehicle configuration may also be determined with the aim of reducing tire rolling resistance. For example, assume that the vehicle includes one or more lift axles or active suspension systems that allow the VCU to adjust the normal load on different axles or even on individual tires. In this case, a normal load distribution that results in reduced tire wear may be selected instead of a configuration that results in a higher degree of tire wear. Accordingly, tire wear of the vehicle 100 may be reduced, which is an advantage.

According to aspects, the one or more estimated tire parameters Sc21 include any one of the following: tire wear, tire longitudinal stiffness, tire lateral stiffness, tire rolling resistance, tire peak friction, tire rolling radius, tire ground contact surface properties, tire balance properties, and wheel alignment properties. These tire parameters may be used to "customize" a tire model to fit a given tire. Such a tire model will provide a more accurate mapping between vehicle operating conditions and tire rolling resistance than a more general tire model that is not tailored to accommodate a given tire. Advantageously, the tire model presented herein may be iteratively updated Sc22 for at least a portion of one or more tire parameters based on the input data. Thus, if the tire properties change over time, the model will also change in order to maintain an accurate mapping between vehicle operating conditions and tire rolling resistance.

There are many different examples as to how the vehicle control can be adjusted to take into account the tire rolling resistance, as given by the tire model in accordance with the vehicle operating state. The tire rolling resistance may be determined for both the current vehicle state, i.e., the extent to which the current vehicle state affects the tire in terms of tire wear, and predicted for future vehicle operation. For example, assume that the vehicle is about to turn and there are several different options at the time of the turn, namely steering by braking, steering by steering an axle, or a combination of both. The tire model may then be queried to determine tire wear associated with the different control options, and the option associated with the smallest tire rolling resistance may be selected. It will be appreciated that if the tire model is also configured to output data relating to, for example, rolling resistance, a combination of two selection criteria may be used in order to find a control option having a reasonable amount of tire wear while providing an acceptable degree of rolling resistance.

The method optionally includes any one of the following: the Sc51 wheel slip is controlled according to the rolling resistance corresponding to the vehicle motion state, the Sc52 normal load is controlled according to the rolling resistance corresponding to the vehicle motion state, for example, by adjusting the setting of the liftable axle of the vehicle according to the rolling resistance and/or the setting of the active suspension system. The method optionally further comprises any one of the following: controlling the bS53 wheel rotational speed as a function of the rolling resistance, controlling movement of the Sc54 heavy vehicle based on the configured target rolling resistance, and coordinating one or more movement support devices of the Sc55 heavy vehicle 100 to reduce tire rolling resistance under constraints including meeting movement requests.

Vehicle control may also be performed at maximum or at least preferred stopping distance requirements, i.e. it may be required that the vehicle is able to stop completely within a specified distance. In such a case, the method may include coordinating one or more motion support devices of the Sc56 heavy vehicle 100 to reduce the stopping distance of the heavy vehicle 100.

It should be appreciated that the method steps discussed above in connection with fig. 6A-6C may be freely combined.

Fig. 7 schematically illustrates components of a control unit 700, such as any of the VUCs 130, 140, in terms of a number of functional units, according to embodiments discussed herein. The control unit 700 may be included in the articulated vehicle 1. The processing circuit 710 is provided using any combination of one or more of a suitable central processing unit CPU, multiprocessor, microcontroller, digital signal processor DSP, etc., capable of executing software instructions stored in a computer program product, for example in the form of a storage medium 730. The processing circuit 710 may further be provided as at least one application specific integrated circuit ASIC or field programmable gate array FPGA.

In particular, the processing circuit 710 is configured to cause the control unit 700 to perform a set of operations or steps, such as the method discussed in connection with fig. 7. For example, the storage medium 730 may store the set of operations, and the processing circuit 710 may be configured to retrieve the set of operations from the storage medium 730 to cause the control unit 700 to perform the set of operations. The set of operations may be provided as a set of executable instructions. Thus, the processing circuit 710 is thereby arranged to perform the method as disclosed herein.

Storage medium 730 may also include persistent storage, which may be any one or combination of magnetic memory, optical memory, solid state memory, or even remotely mounted memory, for example.

The control unit 700 may further include an interface 720 for communicating with at least one external device. Accordingly, interface 720 may include one or more transmitters and receivers, including analog and digital components, as well as a suitable number of ports for wired or wireless communications.

The processing circuit 710 controls the general operation of the control unit 700, for example, by sending data and control signals to the interface 720 and the storage medium 730, by receiving data and reports from the interface 720, and by retrieving data and instructions from the storage medium 730. Other components of the control node and related functionality are omitted so as not to obscure the concepts presented herein.

Fig. 8 shows a computer-readable medium 810 carrying a computer program comprising program code means 820 for performing the methods shown in fig. 6A to 6C when said program product is run on a computer. The computer readable medium and the code means may together form a computer program product 800.

Claims

1. A method for controlling movement of a heavy vehicle (100), the method comprising

Obtaining (Sa 1) input data (561, 562) related to one or more parameters of a tyre (150, 160, 170) on said heavy vehicle (100),

determining (Sa 2) at least part of said one or more tyre parameters based on said input data,

configuring (Sa 3) a tire model, wherein the tire model defines a relationship between wheel slip and generated wheel force, wherein the tire model is parameterized by the one or more tire parameters, and

-controlling (Sa 4) the movement of the heavy vehicle based on the relation between wheel slip and generated wheel force.

2. The method according to claim 1, wherein the input data (Sa 11) comprises input data from one or more sensors (510) arranged to measure one or more operating parameters of the tyre.

3. The method of claim 2, wherein the one or more operating parameters comprise any of: vehicle speed, wheel rotational speed, tire pressure, tire temperature, tire acceleration, tire strain, tire GPS location, weather, ambient temperature, rain classification data, normal load, slip angle, steering angle, and applied torque.

4. The method according to any preceding claim, wherein the input data (Sa 12) comprises data relating to the tyre design obtained from a memory (565).

5. The method of claim 4, wherein the data related to tire design comprises any one of: tire nominal size, tire structural characteristics, tire chemical composition, and tire history.

6. The method according to any preceding claim, wherein the one or more estimated tyre parameters (Sa 21) comprise any one of the following: tire wear, tire longitudinal stiffness, tire lateral stiffness, tire rolling resistance, tire peak friction, tire rolling radius, tire ground contact surface properties, tire balance properties, and wheel alignment properties.

7. A method as claimed in any preceding claim, comprising repeatedly updating (Sa 22) at least part of said one or more tyre parameters based on updated input data.

8. The method according to any preceding claim, wherein the tyre model (Sa 31) is configured to define a relationship between wheel slip and generated wheel forces in a longitudinal direction and a transverse direction.

9. The method according to any preceding claim, wherein the tyre model (Sa 32) is configured to model the rolling resistance of the tyre.

10. The method according to any preceding claim, wherein the tyre model (Sa 33) is configured to model the wear rate of the tyre.

11. The method according to any preceding claim, wherein the tyre model (Sa 34) is configured to define a relationship between wheel slip and both propulsion and braking wheel forces.

12. The method according to any preceding claim, wherein the tyre model (Sa 35) is configured to model the self-aligning torque of the tyre.

13. The method according to any preceding claim, further comprising coordinating (Sa 41) one or more motion support devices of the heavy vehicle (100) to reduce a tire wear rate under constraints comprising meeting a motion request.

14. The method of any preceding claim, further comprising coordinating (Sa 42) one or more motion support devices of the heavy vehicle (100) to reduce tire rolling resistance under constraints comprising meeting motion requests.

15. The method according to any preceding claim, further comprising coordinating (Sa 43) one or more motion support devices of the heavy vehicle (100) to reduce a stopping distance of the heavy vehicle (100).

16. The method according to any preceding claim, further comprising coordinating (Sa 44) one or more motion support devices of the heavy vehicle (100) to increase the mileage capability of the heavy vehicle (100).

17. A computer program (820) comprising program code means for performing the steps of any of claims 1 to 16 when the program is run on a computer or on a processing circuit (810) of a control unit (700).

18. A computer readable medium (810) carrying a computer program (820), the computer program comprising program code means for performing the steps of any one of claims 1 to 16 when the program product is run on a computer or on a processing circuit (810) of a control unit (700).

19. A control unit (130, 140, 700) for determining an allowable vehicle state space of an articulated vehicle (1), the control unit being configured to perform the steps of the method according to any one of claims 1 to 16.

20. A vehicle (100) comprising a control unit (800) according to claim 19.